Leveraging cognitive robotics, advanced vision systems and artificial intelligence, the system autonomously performs tapping tests and multispectral surface inspection along the nonlinear blade to measure and verify the structural integrity with a granularity exceeding thousands of points. Robotized inspection ensures 100 percent accuracy within the self-adaptive process. In contrast, the manual inspection process is labor-intensive, physically demanding and dependent on the experience of the worker.

Each company shared specific competencies to optimize the end-to-end inspection process. These include intelligent algorithms and advanced path planning that allow the robot to see and respond to its surroundings, as well as a comprehensive data acquisition and processing infrastructure that facilitates optimized sound and image recognition. As the blades are mechanically stimulated by the smart robot, the sound response is both recorded and photographed using a multi spectral camera to detect hidden and superficial defects.

Another powerful feature of the system is that it automatically senses the environment. It first localizes the blade, which has been placed on its supports by the operator, detects any obstacles and then calculates both cycle time optimization and collision-free path planning. 

All this technical complexity is hidden behind a simple and effective user interface based on low-code programming. This allows the operator to program the robot using simple, human commands: look for the blade, find the position and execute the action required.